VIDEO: Two Essential Sides Of AI Training

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AI systems are only as good as the training that goes into them – we pointed out a few examples of poorly trained systems last summer. Effective training can be divided into two parts: data and models.

The data is many things. There are utterances – all the words that an enterprise’s customers hand to them; what they said and how they responded. There are customer clickstreams – what did the customer do during and after that session they had, giving you hints and clues to their satisfaction. There is customer context – external data about that customer; plan  or services they subscribe to, did they pay their bill, are they out of the country? whatever you’ve got, all that data you want to gather in and use that to understand your customers need the customer’s history, what are they doing in the past next best offer?

This is all data that is used by analysts, data scientists, content experts, and quality assurance departments to perform AI training and shape the care and service an enterprise can offer to its customers.

The other side is the training models, which extends beyond natural language processing. What’s going to help you refine your understanding of your customer’s needs? Training models need to determine customer satisfaction while simultaneously matching customer context. There is too much data for individual analysis –  tens to hundreds of thousands of transactions every day. Enterprises need a system – a model – that automatically determines what a happy customer looks like through the data in these interactions. This system must be trained by linguists, machine learning experts, research scientists and architects.

In the above video, Wysdom CEO Ian Collins walks us through the differences between the two, how the combine to make up the full spectrum of AI Training, and provides a few real life examples.

If you missed it, check out Part 1 in this series, where Ian explains how Wysdom defines Cognitive Care.

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Artiom Kreimer

VP, Product & Analytics

Artiom has spent 10 years in software and mobile engineering, specializing in quality assurance and customer service. He has worked in testing and QA at both startups and in enterprises such as Clickfree, TELUS, and Freescale Semiconductor.

Michel Benitah

VP, Optimization & Delivery

Michel has 20 years of experience in leading the successful delivery of Conversational AI and Natural Language Customer Care solutions to some of the largest financial, telco, healthcare, utilities, and retail enterprises throughout North America. 


Prior to joining Wysdom, Michel spent 20 years at Nuance Communications, holding senior management and leadership positions within the enterprise division, most recently as director of the Toronto office and professional services team.

Frederic Lam

SVP, Sales

Fred brings in 25 years of international experience in sales and business development across North America, the Caribbean, Asia-Pacific, Europe, and the Middle-East.


Prior to Wysdom.AI, he held sales leadership positions at Oracle, Redknee, and Movius/Glenayre, successfully growing revenues in both large and small organizations. Fred has also been involved in the start-up community in the earlier stages of his career as an Investment Manager with SP Capital and was an alternate director on a few investee companies.

Karen Chan

Chief Engineering Officer, Co-Founder

With 20 years of experience in software and mobile, Karen has held senior technical roles at 5 startups, including Wysdom.AI, Clickfree, Mobile Diagnostix (HP), Teamatic, and Virtualthere.

Karthik Balakrishnan

Chief Technology Officer

Karthik has over a decade of hands-on, proven global expertise in emerging technologies and implementing intricate platforms and solutions for telecommunications and enterprise during his time at Amdocs, with senior positions in their India, Cyprus, America, and Canada offices.

Nitin Singhal

Chief Operating Officer

Nitin has over 20 years of success in global executions of business technology, driving operational efficiency and digital scalability for some of the world’s largest enterprise clients. 


Nitin spent 16 years at Redknee holding executive positions in Research and Development, Customer Operations, Partner Alliances, and most recently as COO.

Jeff Brunet​

President, Co-Founder

Jeff has more than 20 years of experience in the startup world, founding and growing 4 software companies: AracNet, Mobile Diagnostix (HP), ClickFree, and Wysdom.AI. 


His in-depth understanding of software development and the challenges in making new technologies successful in the startup world prove invaluable as he serves on the boards of XMG, SurfEasy (Opera), Locationary (Apple), Groupie, and as an advisor to Pushlife (Google), LogMeIn (IPO) and HP. 


Jeff holds 23 issued patents in the wireless and consumer electronics spaces and is the lead inventor on 30+ pending patents.

Ian Collins​

CEO, Co-Founder

Ian has founded and grown 6 technology companies over the past 20 years, primarily in the enterprise software space including Wyrex, Mobile Diagnostix (HP), Clickfree, and most recently Wysdom.AI. 


Ian invests, mentors, and sits on the boards of several startups in the Toronto area.